US8649457B2ActiveUtilityA1
Precoding process for a transmitter of a MU-MIMO communication system
Est. expiryJul 21, 2029(~3 yrs left)· nominal 20-yr term from priority
H04B 7/0465H04B 7/0452H04L 25/03343
31
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Cited by
11
References
10
Claims
Abstract
A Precoding process for a transmitter of a MU-MIMO communication system comprising M antennas in the transmitter and K User Equipments (UE), said precoding being based on a Regularized Zero Forcing (R-ZF) linear precoding.
Claims
exact text as granted — not AI-modifiedThe invention claimed is:
1. Precoding process for a transmitter of a MU-MIMO communication system comprising:
M antennas in the transmitter and K User Equipments (UE), said precoding being based on a Regularized Zero Forcing (R-ZF) linear precoding of the type:
G
=
H
H
(
HH
H
+
M
α
I
K
)
-
1
=
(
H
H
H
+
M
α
I
M
)
-
1
H
H
With:
H being a complex matrix representative of the K×M channel estimates, said H matrix comprising channel coefficients which are correlated with corresponding correlation coefficients being the entries of a correlation matrix ⊖ T ,
I K and I M being the identity matrix, respectively of size K×K and M×M;
And α being the regularization parameter,
wherein α is computed as follows:
a) computing the correlation matrix ⊖ T ;
b) initializing two parameters α max and α min ;
c) computing α=½(α max +α min );
d) determining ( 140 ) for z=−α the value of S (S H′ ω Θ T H′ ω H (z)) solving the fixed-point equation:
S
(
z
)
=
(
∫
λ
μ
Θ
T
(
λ
)
ⅆ
λ
1
+
λ
β
S
(
z
)
-
z
)
-
1
With λ being the eigenvalues of the correlation matrix ⊖ T , μ being the empirical eigenvalue distribution functions of ⊖ T and β being M/K;
e) determining for z=−α the value of S d
(
ⅆ
ⅆ
x
S
H
w
′
Θ
T
H
w
′
H
(
z
)
)
solving the fixed-point equation:
S
d
(
z
)
=
1
+
∫
λ
2
β
S
d
(
z
)
(
1
+
λ
β
S
(
z
)
)
2
μ
Θ
T
(
λ
)
ⅆ
λ
(
S
(
z
)
)
-
2
f) computing the equation
F
=
S
β
+
β
-
1
β
α
-
α
(
S
d
β
+
β
-
1
β
α
2
)
g) adapting the interval [α min , α max ] as follows:
if F−P<0, with P being the total available transmit power, then computing ( 180 ) α max =α, otherwise computing α min =α.
2. Precoding process according to claim 1 wherein step a is computed by a WHILE loop used for computing the regularization parameter α of the precoding process, said WHILE loop being executed as long as the absolute value of F−P (ABS(F−P)) is superior to a predetermined value ε.
3. Precoding process according to claim 2 , wherein step d is performed by a first FOR loop executed for a number of N occurrences, said first FOR loop comprising the steps of:
initializing S to a predetermined value;
performing, for n=1 to N, the following computation:
S
=
(
α
+
1
M
∑
i
=
1
M
λ
i
1
+
λ
i
β
S
)
-
1
.
4. Precoding process according to claim 3 , wherein step e is performed by a second FOR loop which is executed for a number of N occurrences, said second FOR loop comprising the steps of:
initializing S d to a predetermined value;
performing, for n=1 to N, the following computation:
S
d
=
(
1
+
1
M
∑
i
=
1
M
λ
i
2
β
S
d
(
1
+
λ
i
β
S
)
2
)
·
S
2
.
5. Precoding process in accordance to claim 1 wherein K=M.
6. Transmitter for a MU-MIMO communication system comprising M antennas in the transmitter and K User Equipments (UE), said precoding being based on a Regularized Zero Forcing (R-ZF) linear precoding of the type:
G
=
H
H
(
HH
H
+
M
α
I
K
)
-
1
=
(
H
H
H
+
M
α
I
M
)
-
1
H
H
With:
H being a complex matrix representative of the K×M channel estimates, said H matrix comprising channel coefficients which are correlated with corresponding correlation coefficients being the entries of a correlation matrix ⊖ T ,
I K and I M being the identity matrix, respectively of size K×K and M×M;
And α being the regularization parameter,
said transmitter being characterized in that it comprises:
means for computing the correlation matrix ⊖ T ;
means for initializing the two parameters α max and α min
means for computing α=½(α max +α min );
means for determining for z=−α the value of S solving the fixed-point equation:
S
(
z
)
=
(
∫
λ
μ
Θ
T
(
λ
)
ⅆ
λ
1
+
λ
β
S
(
z
)
-
z
)
-
1
means for determining for z=−α the value of S d
(
ⅆ
ⅆ
x
S
H
w
′
Θ
T
H
w
′
H
(
z
)
)
solving the fixed-point equation:
S
d
(
z
)
=
1
+
∫
λ
2
β
S
d
(
z
)
(
1
+
λ
β
S
(
z
)
)
2
μ
Θ
T
(
λ
)
ⅆ
λ
(
S
(
z
)
)
-
2
means for computing the equation
F
=
S
β
+
β
-
1
β
α
-
α
(
S
d
β
+
β
-
1
β
α
2
)
means for adapting the interval [α min , α max ] by using the following process:
if F−P<0, with P being the total available transmit power, then compute α max =α, otherwise compute α min =α.
7. Transmitter according to claim 6 wherein it includes means for performing a WHILE loop used for computing the regularization parameter α of the precoding process, said WHILE loop being executed as long as the absolute value of F−P (ABS(F−P)) is superior to a predetermined value ε.
8. Transmitter according to claim 7 wherein it further includes means for performing by a first FOR loop executed for a number of N occurrences, further comprising:
means for initializing S to a predetermined value;
means for performing, for n=1 to N, the following computation:
S
=
(
α
+
1
M
∑
i
=
1
M
λ
i
1
+
λ
i
β
S
)
-
1
.
9. Transmitter according to claim 8 further comprising means for executing a second FOR loop for a number of N occurrences which includes:
means for initializing S d to a predetermined value;
means for performing, for n=1 to N, the following computation:
S
d
=
(
1
+
1
M
∑
i
=
1
M
λ
i
2
β
S
d
(
1
+
λ
i
β
S
)
2
)
·
S
2
.
10. Transmitter according to claim 6 wherein K=M.Cited by (0)
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